Examples of org.apache.cassandra.utils.MerkleTree$MerkleTreeSerializer

org.apache.cassandra.utils.MerkleTree
A MerkleTree implemented as a binary tree. A MerkleTree is a full binary tree that represents a perfect binary tree of depth 'hashdepth'. In a perfect binary tree, each leaf contains a sequentially hashed range, and each inner node contains the binary hash of its two children. In the MerkleTree, many ranges will not be split to the full depth of the perfect binary tree: the leaves of this tree are Leaf objects, which contain the computed values of the nodes that would be below them if the tree were perfect. The hash values of the inner nodes of the MerkleTree are calculated lazily based on their children when the hash of a range is requested with hash(range). Inputs passed to TreeRange.validate should be calculated using a very secure hash, because all hashing internal to the tree is accomplished using XOR. If two MerkleTrees have the same hashdepth, they represent a perfect tree of the same depth, and can always be compared, regardless of size or splits.

        Validator validator = new Validator(new CFPair(tablename, cfname));
        validator.prepare(store);
        validator.complete();


        // grab reference to the tree
        MerkleTree tree = validator.tree;


        // notify ourself (should immediately be delivered into AE_STAGE)
        aes.notifyNeighbors(validator, LOCAL, Arrays.asList(LOCAL));
        flushAES().get(5, TimeUnit.SECONDS);

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    {
        // generate a tree
        Validator validator = new Validator(new CFPair(tablename, cfname));
        validator.prepare(store);
        validator.complete();
        MerkleTree ltree = validator.tree;


        // and a clone
        validator = new Validator(new CFPair(tablename, cfname));
        validator.prepare(store);
        validator.complete();
        MerkleTree rtree = validator.tree;


        // change a range we own in one of the trees
        Token ltoken = StorageService.instance.getLocalToken();
        ltree.invalidate(ltoken);
        MerkleTree.TreeRange changed = ltree.invalids(StorageService.instance.getLocalPrimaryRange()).next();

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        // generate a tree
        Validator validator = new Validator(request);
        validator.prepare(store);
        validator.complete();
        MerkleTree ltree = validator.tree;


        // and a clone
        validator = new Validator(request);
        validator.prepare(store);
        validator.complete();
        MerkleTree rtree = validator.tree;


        // change a range in one of the trees
        Token ltoken = StorageService.getPartitioner().midpoint(local_range.left, local_range.right);
        ltree.invalidate(ltoken);
        MerkleTree.TreeRange changed = ltree.get(ltoken);

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    {
        // generate a tree
        Validator validator = new Validator(request);
        validator.prepare(store);
        validator.complete();
        MerkleTree ltree = validator.tree;


        // and a clone
        validator = new Validator(request);
        validator.prepare(store);
        validator.complete();
        MerkleTree rtree = validator.tree;


        // change a range we own in one of the trees
        Token ltoken = StorageService.instance.getLocalToken();
        ltree.invalidate(ltoken);
        MerkleTree.TreeRange changed = ltree.invalids(StorageService.instance.getLocalPrimaryRange()).next();

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        Validator validator = new Validator(new CFPair(tablename, cfname));
        validator.prepare();
        validator.complete();


        // grab reference to the tree
        MerkleTree tree = validator.tree;


        // notify ourself (should immediately be delivered into AE_STAGE)
        aes.notifyNeighbors(validator, LOCAL, Arrays.asList(LOCAL));
        flushAES().get(5, TimeUnit.SECONDS);

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        Validator validator = new Validator(new CFPair("Keyspace1", "lcf"));
        validator.prepare();


        // create a clone with no values filled
        validator.complete();
        MerkleTree ltree = validator.tree;
        validator = new Validator(new CFPair("Keyspace1", "rcf"));
        validator.prepare();
        validator.complete();
        MerkleTree rtree = validator.tree;


        // change a range in one of the trees
        Token min = StorageService.instance.getPartitioner().getMinimumToken();
        ltree.invalidate(min);
        MerkleTree.TreeRange changed = ltree.invalids(new Range(min, min)).next();

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        // with two SSTables
        ColumnFamilyStoreUtils.writeColumnFamily(rms);
        ColumnFamilyStore store = ColumnFamilyStoreUtils.writeColumnFamily(rms);
        
        // force a major compaction, and wait for it to finish
        MerkleTree old = aes.getCachedTree(tablename, cfname, LOCAL);
        CompactionManager.instance().submitMajor(store, 0).get(5000, TimeUnit.MILLISECONDS);


        // check that a tree was created and cached
        flushAES().get(5000, TimeUnit.MILLISECONDS);
        assert old != aes.getCachedTree(tablename, cfname, LOCAL);

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        Validator validator = new Validator(new CFTuple(tablename, cfname), LOCAL);
        validator.prepare();
        validator.complete();


        // grab reference to the tree
        MerkleTree tree = validator.tree;


        // notify ourself (should immediately be delivered into AE_STAGE)
        aes.notifyNeighbors(validator, LOCAL, Arrays.asList(LOCAL));
        flushAES().get(5, TimeUnit.SECONDS);

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        validator.prepare();


        // create a clone with no values filled


        validator.complete();
        MerkleTree ltree = validator.tree;
        validator = new Validator(new CFTuple("rtable", "rcf"), LOCAL);
        validator.prepare();
        validator.complete();
        MerkleTree rtree = validator.tree;


        // change a range in one of the trees
        Token min = StorageService.instance().getPartitioner().getMinimumToken();
        ltree.invalidate(min);
        MerkleTree.TreeRange changed = ltree.invalids(new Range(min, min)).next();

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    @Before
    public void clear()
    {
        TOKEN_SCALE = new BigInteger("8");
        partitioner = new RandomPartitioner();
        mt = new MerkleTree(partitioner, RECOMMENDED_DEPTH, Integer.MAX_VALUE);
    }

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Related Classes of org.apache.cassandra.utils.MerkleTree$MerkleTreeSerializer

org.apache.cassandra.dht.IPartitioner

org.apache.cassandra.dht.Range

org.apache.cassandra.dht.Token

org.apache.cassandra.repair.DifferencerTest

org.apache.cassandra.repair.LocalSyncTaskTest

org.apache.cassandra.repair.messages.ValidationComplete$ValidationCompleteSerializer

org.apache.cassandra.repair.Validator

org.apache.cassandra.repair.ValidatorTest

org.apache.cassandra.service.AntiEntropyService

org.apache.cassandra.service.AntiEntropyService$TreeRequestVerbHandler

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